Second order elastic metrics on the shape space of curves
For researchers in shape analysis, this provides the first numerical tools for second-order elastic metrics, which have theoretical completeness advantages over lower-order metrics.
The paper presents algorithms for numerically solving geodesic initial and boundary value problems for second-order Sobolev metrics on planar curves, enabling Karcher mean computation. The framework allows free choice of metric constants and is demonstrated on physical object shapes.
Second order Sobolev metrics on the space of regular unparametrized planar curves have several desirable completeness properties not present in lower order metrics, but numerics are still largely missing. In this paper, we present algorithms to numerically solve the initial and boundary value problems for geodesics. The combination of these algorithms allows to compute Karcher means in a Riemannian gradient-based optimization scheme. Our framework has the advantage that the constants determining the weights of the zero, first, and second order terms of the metric can be chosen freely. Moreover, due to its generality, it could be applied to more general spaces of mapping. We demonstrate the effectiveness of our approach by analyzing a collection of shapes representing physical objects.